How AI (not automation) will revolutionize commercial trucking
The AI market for the transportation industry is big and getting a lot bigger. In fact, it’s projected to grow at a compound annual rate of nearly 18% from 2017 to 2030, with its size increasing to $10.3 billion by 2030.
Commercial trucking, beset with labor shortages and safety concerns, stands to benefit enormously, but the adoption curve is steep. While the buzz around autonomous trucks has made headlines, the reality is that AI will have a much larger impact for the foreseeable future, but it’s implementation will also present challenges — challenges that have echoes in just about any industry or sector confronting a major digital transformation.
I caught up with Avi Geller, CEO of fleet management company Maven (Machines) and MIT alum, who believes that AI is central to solving some of the logistics industry’s most pressing problems and creating efficiencies not possible before. His insights are a master class on the changes and opportunities confronting one of the sectors that’s become a canary in the coal mine for AI implementation.
GN: Heading into 2021, what are the most pressing problems facing the trucking and logistics sectors? Another way to phrase this, where are the opportunities for innovation?
Avi Geller: The opportunities for innovation within the trucking and logistics sectors are endless. As an industry that has been transforming with the advent of digital solutions, companies are now reaping the benefits of technology. Some of the most important examples of digital transformation and technological implementation relate to core operational capabilities in trucking. For example, planning, route optimization, and mobile workflow tools that are used by fleets via software applications have already started demonstrating the benefits of innovation and solving some of the most pressing problems, and they will continue to do so in the future.
Route optimization software, strengthened by ongoing advancements in AI and machine learning, will continue to provide fleets with an abundance of knowledge and efficiency gains. The ability to automatically plan and optimize routes significantly better than before — all while taking the data and variables into account that only route planners and dispatchers typically know, like driver skillset and which routes are the most challenging — will give planners and dispatchers more time to focus on the unique cases that require advanced planning experience.
The concept of a “workflow” isn’t new. However, truck drivers haven’t always been enabled with a mobile-first workflow experience to guide them through the right steps for each stop they make on a trip. Opportunities exist to enable drivers with technology that makes their lives easier so that they can focus more on driving. Improving the driver experience has become an increasingly important initiative for fleets as they look for ways to combat the national driver shortage and retain their drivers. In turn, these cloud-based software solutions also keep fleet managers abreast of driver productivity in real time. This is a win-win for both fleet managers and drivers.
GN: What are some ways that AI, as opposed to full autonomy, can help address these problems/opportunities? Are we talking about in-truck solutions, dispatch solutions, or both?
Avi Geller: AI can be used for both in-truck and dispatch solutions. From a driver’s perspective, we can use AI to build a better route for them, and increasingly, positively impact the kind of decisions that they make. It goes deeper than determining when a driver should arrive at a destination on their route though. AI algorithms can help predict the ideal time of day to schedule a delivery, taking into account a variety of factors, such as when the shipper is the least busy so that a driver is less likely to have to wait in line at a loading facility. Fleets can use AI to help drivers be more productive, while also increasing fleetwide efficiency.
